Waterloo Soft Matter Theory Conference

This is a new one-day conference on soft matter theory. This will bring in Canadian researchers and graduate students in this area to showcase their research projects and promote collaborations. The relevant topics include polymers, membranes, materials, and nano-science. The overall format will be two keynote speakers (one morning and one afternoon) and seven invited speakers. There will be a special 90-minute session, where the graduate students can make short oral presentations on their research projects. Lunch will be provided by the Black Hole Bistro.

Randall Kamien, University of PennsylvaniaDavid Weitz, Harvard University

Invited Speakers:

John Bechhoefer, Simon Fraser UniversityColin Denniston, University of Western OntarioMark Matsen, University of WaterlooNikolas Provatas, McGill UniversityJoerg Rottler, University of British ColumbiaAndrew Rutenberg, Dalhousie UniversityAn-Chang Shi, McMaster UniversityGary Slater, University of Ottawa

Tyler Shendruk, University of OttawaElectrophoretic Mobility within a Confining Well

Theater

5:38-5:44pm

Russell Spencer, University of GuelphDynamical simulation of disordered micelles in a diblock copolymer melt with fluctuations

Theater

5:44-5:50pm

Yu-Cheng Su, University of WaterlooBudding transition of a self-avoiding polymer confined by a soft membrane adhering onto a flat wall

Theater

5:50-5:56pm

John Tatini Titantah,University of Western OntarioAb initio insight in supercooled water

Theater

5:56-6:02pm

Shaghayegh Vafaei, University of GuelphCalculating the free energy of antimicrobial peptide (HHC-36) dimerization in bulk

Theater

6:10pm

Conference Banquet

Bistro – 1st Floor

John Bechhoefer, Simon Fraser University

Inferring the spatiotemporal DNA replication program from noisy data

In eukaryotic organisms, DNA replication is initiated at “origins,” launching “forks” that spread bidirectionally to replicate the genome. The distribution and firing rate of these origins and the fork progression velocity form the “replication program.” With Antoine Baker, I generalize a stochastic model of DNA replication to allow for space and time variations in origin-initiation rates, characterized by a function I(x,t). We then address the inverse problem of inferring I(x,t) from experimental data concerning replication in cell populations. Previous work based on curve fitting depended on arbitrarily chosen functional forms for I(x,t), with free parameters that were constrained by the data. We introduce a model-free, non-parametric method of inference that is based on Gaussian process regression, a well-known inference technique from the machine-learning community. The method replaces specific assumptions about the functional form of the initiation rate with more general prior expectations about the smoothness of variation of this rate, along the genome and in time. Using this inference method, we can recover simulated replication schemes with data that are typical of current experiments without having to know or guess the functional form for the initiation rate I(x,t). I will argue that Gaussian process regression has many other potential applications to physics.

Colin Denniston, University of Western Ontario

Building Colloidal Crystals in Anisotropic Media

Colloids in a liquid crystal matrix exhibit very anisotropic interactions. Further, these interactions can be altered by both properties of the colloid and of the liquid crystal. This gives a potential for creating specific colloidal aggregates and crystals by manipulating the interactions between colloids. However, modelling these interacting colloids in a liquid crystal is very challenging. We use a hybrid particle-lattice Boltzmann scheme that incorporates hydrodynamic forces and forces from the liquid crystal field. I will discuss configurations that we have studied, including chains and a potentially stable colloidal crystal with a diamond lattice structure.

Monte Carlo field-theoretic simulations (MC-FTS) are performed on melts of symmetric diblock copolymer for invariant polymerization indexes extending down to experimentally relevant values of N=104. The simulations are performed with a fluctuating composition field, W-(r), and a pressure field, W+(r), that follows the saddle-point approximation. Our study focuses on the disordered-state structure function, S(k), and the order-disorder transition (ODT). Although short-wavelength fluctuations cause an ultraviolet (UV) divergence in three dimensions, this is readily compensated for with the use of an effective Flory-Huggins interaction parameter, e. The resulting S(k) matches the predictions of renormalized one-loop (ROL) calculations over the full range of eN and N examined in our study, and agrees well with Fredrickson-Helfand (F-H) theory near the ODT. Consistent with the F-H theory, the ODT is discontinuous for finite N and the shift in (eN)ODT follows the predicted N-1/3 scaling over our range of N.

Nikolas Provatas, McGill University

Modelling Materials Microstructure Across Scales using Phase Field Methods

Phase field crystal models and their recent extension will be summarized. Their application to non-equilibrium kinetics and phase transformations in materials will be reviewed. In particular, we review new results from applications of this modeling paradigm to solute trapping during rapid solidification of alloys, defect-mediated solid-state precipitation, and magneto-crystalline interactions. We close with a discussion of new complex amplitude representations of PFC models and how these can be used for multi-scale simulations using adaptive mesh refinement methods.

Joerg Rottler, University of British Columbia

Predicting plasticity with soft vibrational modes: from dislocations to glasses

We show how to utilize soft modes in the vibrational spectrum as a universal tool for the identification of defects in solids. Perfect crystals with isolated dislocations exhibit single phonon modes that localize at the dislocation core, and their polarization pattern predicts the motion of atoms during elementary dislocation glide in two and three dimensions in great detail. A superposition of soft modes can be used to construct a population of soft spots that predict the location of local plastic rearrangements at the grain boundaries of polycrystals and in amorphous solids. Additionally, we find a significant correlation between the soft directions of the polarization fields and the atomic displacements that result from elementary shear events.

We have modelled stress concentration around small gaps in anisotropic elastic sheets, corresponding to the peptidoglycan sacculus of bacterial cells, under loading corresponding to the effects of turgor pressure in rod-shaped bacteria. We find that under normal conditions the stress concentration is insufficient to mechanically rupture bacteria, even for gaps up to a micron in length. We then explored the effects of stress-dependent smart-autolysins, as hypothesised by Arthur L Koch. We show that the measured anisotropic elasticity of the PG sacculus can lead to stable circumferential propagation of small gaps in the sacculus. This is consistent with the recent observation of circumferential propagation of PG-associated MreB patches in rod-shaped bacteria. We also find a bistable regime of both circumferential and axial gap propagation, which agrees with behavior reported in cytoskeletal mutants of B. subtilis. We conclude that the elastic anisotropies of a bacterial sacculus, as characterised experimentally, may be relevant for maintaining rod-shaped bacterial growth.

An-Chang Shi, McMaster University

Transition Pathways Connecting Stable and Metastable Phases

Phase transitions are ubiquitous in nature. Understanding the kinetic pathways of phase transitions has been a challenging problem in physics and physical chemistry. From a thermodynamics point of view, the kinetics of phase transitions is dictated by the characteristics of the free energy landscape. In particular, the emergence of a stable phase from a metastable phase follows specific paths, the minimum energy paths, on the free energy landscape. I will describe the characteristics of the minimum energy paths and introduce an efficient method, the string method, to construct them. I will use self-assembled phases of block copolymers as examples to demonstrate the power of the method. In particular, I will show how precisely determined transition pathways provide understanding and surprises when we try to connect the different ordered phases of block copolymers.

Gary Slater, University of Ottawa

Polymer translocation : alternative driving forces

David Weitz, Harvard University

Slow Melting and Fast Crystals

This talk will focus on the behavior of colloidal crystals, and will describe both the nucleation and growth of crystals and their melting. The nucleation and growth of colloidal crystals is experimentally observed to be much faster than expected theoretically or through simulation. The discrepancy can be as much as 10150! I will describe some new experiments that suggest a possible reason for this. I will also describe the melting of colloidal crystals formed with highly charged particles that form a Wigner lattice. I will show that this melting resembles a second-order phase transition, and follows the prediction of Born for a catastrophic collapse of the elastic constant.

Electrostatic phenomena in soft matter systems are often intriguing or even counterintuitive. DNA condensation by polyvalent counterions is now a classic example by which highly-negatively charged DNA strands attract each other in the presence of poly-cations. Also Mg2+ can stabilize inverted hexagonal phases of lipid aggregates that would otherwise form lamellar phases. Here we discuss another intriguing electrostatic phenomenon: electrostatic modification of lipid membranes by poly-cations.

While successfully reproducing hydrophobic and hydrophilic interactions the Martini model is insufficient to keep a protein folded as it lacks electrostatic interactions. Using split charge equilibration at each time step can yield realistic dynamic bead charges. Combining this with a Drude oscillator based polarization model for all beads will permit modeling of hydrogen bonds to maintain secondary protein structure and will enable more accurate coarse-grained simulations of protein-protein and protein-membrane interactions.

Confinement can influence qualitatively the spatial organization of polymer chains. Cylindrical confinement is of particular interest since it not only stiffens individual chains but also enhances their segregation. Here we discuss a ring copolymer confined in a closed cylindrical space as a model nucleoid (an intracellular space where the bacterial chromosome is confined). When the cylinder and polymer parameters are chosen properly our model explains quantitatively recent experimental results for the spatial organization of the E. coli chromosome.

A thin partially wetting layer of liquid will dewet from an unfavourable substrate resulting in spherical cap shaped droplets next to a microscopically thin residual wetting layer of the liquid. We have measured a discrete spectrum of contact angles for dewetted droplets of a lamellar diblock copolymer in its disordered phase instead of the single unique contact angle that is usually observed. The different contact angles coexist with various thicknesses of wetting layer and the spectrum of measured contact angles shifts as the temperature is raised.

We use coarse-grained molecular-dynamics (MD) simulations to study the fragmentation of sodium dodecyl sulfate micelles under Poiseuille-like flow in a die-extruder geometry. The effect of flow confinement and wetting on spherical micelles is explored. We demonstrate that the interplay between flow and the wettability of the channel determines the size of daughter micelles inside the channel.

Colloidal particles organize spontaneously at fluid interfaces owing to a variety of interactions to form well organized structures that can be exploited to synthesize advanced materials. While the physics of colloidal assembly at isotropic interfaces is well understood the mechanisms that govern interactions between particles at liquid crystal interfaces are not yet clearly established. In particular smectic liquid crystal films offer important degrees of freedom that can be used to direct particles into new structures.

Mineral-associated proteins have been proposed to play a central role not only in assisting the growth of biomineral crystals in hard tissues but also in preventing or limiting mineral formation in soft tissues. The elucidation of protein-biomineral interactions may lead to the design of mineralized tissues with novel properties and most importantly the development of therapies for common diseases such as kidney stones calcification in blood vessels osteoporosis etc. However the mechanism of the interaction at this unique organic-inorganic interface is still poorly understood.

The self-assembled structures formed in binary blends of AB/CD diblock copolymers are studied using self-consistent field theory focusing on cases with attractive A/C and repulsive B/D interactions. The attractive A/C interaction prevents macroscopic phase separation whereas the repulsive B/D interaction promotes B/D separation leading to the formation of complex hierarchical structures. The combination of these features makes the AB/CD blend an ideal model system for the study of hierarchical self-assembly.

Wang et al.
[PNAS 106 (2009) 15160] have found that in several systems, the linear time
dependence of mean-square displacement (MSD) of diffusing colloidal particles,
typical of normal diffusion, is accompanied by a non-Gaussian displacement
distribution (DD), with roughly exponential tails at short times, a situation
termed “anomalous yet Brownian” diffusion. We point out that lack of “direction
memory” in the particle trajectory (a jump in a particular direction does not